From p.gleeson at ucl.ac.uk Wed Aug 25 16:23:41 2010 From: p.gleeson at ucl.ac.uk (Padraig Gleeson) Date: Wed, 25 Aug 2010 16:23:41 +0100 Subject: [neuroConstruct] New version neuroConstruct, two new NeuroML models & update to ChannelML NEURON mod file mapping Message-ID: <4C75357D.6000300@ucl.ac.uk> Hi, A few recent developments: 1) A new version of neuroConstruct, v1.4.1, is available at http://www.neuroconstruct.org. This contains minor updates to the core application, full details are here: http://www.neuroconstruct.org/nCinfo/RELEASE_NOTES One potentially useful addition in this version is the ability to load valid NeuroML files using the command line option -neuroml: ./nC.sh -neuroml MyNeuroML.xml (or nC.bat -neuroml MyNeuroML.xml for Windows, see http://www.neuroconstruct.org/docs/install.html). This will create a new neuroConstruct project containing all the elements from the NeuroML file. For one containing a full model description of cells, channels, network structure etc. the neuroConstruct project is populated with all of the elements required for generating the model in NEURON, GENESIS, etc. and default values of simulation duration, dt and plots of membrane potential are added (including a -sedml option for loading this info from a SED-ML file is in the pipeline). Some restrictions apply as usual: a NetworkML only file needs to be loaded (via the menu) into a project containing cell groups and network connections with the names of the populations/projections, etc.; template based NetworkML representations are not yet supported. 2) Two new projects are included with this release, and are also available here http://www.neuroconstruct.org/models/index.html. SolinasEtAl_GolgiCell is an implementation in NeuroML of the abstract Golgi cell model from Solinas et al. 2007: Computational reconstruction of pacemaking and intrinsic electroresponsiveness in cerebellar Golgi cells. Front Cell Neurosci. VervaekeEtAl-GolgiCellNetwork is a project containing a number of Golgi cell models with detailed reconstructed morphologies, and featured in a recent paper in Neuron: Rapid Desynchronization of an Electrically Coupled Interneuron Network with Sparse Excitatory Synaptic Input: http://www.cell.com/neuron/abstract/S0896-6273%2810%2900512-X. Both of these models can be fully expressed in NeuroML, but at this time only run on NEURON due to the complexity of the multistate SK channel (see below). 3) The XSL mapping file to generate NEURON mod files from ChannelML files (ChannelML_v1.8.1_NEURONmod.xsl) has been updated with the following two changes (note the specification for ChannelML v1.8.1 is unchanged, these changes just increase the scope of models that are supported by NEURON mod files) a) Mapping of multi state (more than the 1 open & 1 closed state in HH) kinetic scheme descriptions to mod files is now supported. Previously these could only be mapped to NEURON ChannelBuilder format, but now they can be used for generating mod files using the KINETIC block and statements like: ~ n0 <-> n1 (alpha_n0_n1, beta_n0_n1), e.g. the 5 start representation of the squid axon K channel: http://www.neuroml.org/NeuroMLValidator/ViewNeuroMLFile.jsp?localFile=NeuroMLFiles/Examples/ChannelML/KChan_KineticScheme.xml is mapped to: http://www.neuroml.org/NeuroMLValidator/Transform.jsp?localFile=NeuroMLFiles/Examples/ChannelML/KChan_KineticScheme.xml&xslFile=NeuroMLFiles/Schemata/v1.8.1/Level2/ChannelML_v1.8.1_NEURONmod.xsl Another example of such a channel is the multistate SK/afterhyperpolarising K+ current from Solinas et al 2007, which has state transitions dependent on Ca2+ concentration: http://www.neuroml.org/NeuroMLValidator/Transform.jsp?localFile=NeuroMLFiles/Examples/ChannelML/SK_KineticScheme.xml&xslFile=NeuroMLFiles/Schemata/v1.8.1/Level3/NeuroML_Level3_v1.8.1_HTML.xsl This type of channel cannot (yet) be mapped to the old Channel Builder format, or indeed GENESIS, MOOSE or PSICS. b) The mapping of a decaying calcium concentration pool in an element is also updated. See for an example: http://www.neuroml.org/NeuroMLValidator/Transform.jsp?localFile=NeuroMLFiles/Examples/ChannelML/CaPool.xml&xslFile=NeuroMLFiles/Schemata/v1.8.1/Level2/ChannelML_v1.8.1_NEURONmod.xsl This mechanism now performs a check whether the section it's been placed on is a sphere or a cylinder: if the surface area is given by pi * diam * diam it assumes the section is meant to be a sphere, if not it assumes the section is a cylinder. This distinction is unimportant for the calculation of total conductance from max cond density (surf area of sphere of diam d is same as cylinder of length = diam = d), because if the model is of a pool of calcium just below the surface of thickness t, this pool volume is slightly different if the section is a sphere or cylinder. I believe the latest version covers most cases sufficiently well. The only problems may arise when a user wants a section with diam = length, wants it to be modelled as a cylinder (with no area on the ends) and has a relatively large thickness for the volume of calcium. Regards, Padraig ----------------------------------------------------- Padraig Gleeson Room 321, Anatomy Building Department of Neuroscience, Physiology& Pharmacology University College London Gower Street London WC1E 6BT United Kingdom +44 207 679 3214 p.gleeson at ucl.ac.uk -----------------------------------------------------